This job might no longer be available.

Data Scientist

Job Summary:

As the video game industry moves towards the Games-as-a-Service model, it becomes crucial to prepare successful marketing plans and strategies to enable the growth of publishers’ player base and optimise player engagement.

Square Enix’s Analytics & Insights department supports the design of these strategies, using data collected from its players and games. Our expanding team consists of skilled and passionate analysts and data scientists working across a wide range of projects for game production, marketing, web, sales and executive teams. Our team’s mission is to enable our stakeholders to make data-driven decisions, ultimately leading to better games through data insights.

We are looking for a curious and adaptable Data Scientist who will leverage a range of data sources to impact user support, in-game and external promotions and to improve our players’ game experience. Such as:

• How do we predict a player’s likelihood to churn? Can we prevent this from happening? If not, how do we win them back?
• How to cross-sell and up-sell our games and merchandise? Which is the most effective marketing channel for this purpose?
• Is a game well balanced? Is it fun to play the game? How can we measure and optimise for this?
• How can we automate communications and personalise messaging to our customers?

You will be able to confidently use traditional approaches (Statistical testing, Linear regression and mathematical modelling) and distinguish noise and signal, to find actionable insights. Also, they will apply ML approaches to multi-sourced large dataset to improve the customer experience in our acquisition channel, game and eCRM.

You are required to have strong coding skills. You will work on cloud computing environment (Kafka, Beam, Airflow and BigQuery).

We will provide you with a structured development plan and regular reviews to ensure you meet your goals.

Requirements

Key Deliverables:

• Dive deep into game behaviour data to identify key opportunities for game improvement and enhancement of our communication with players
• Build Machine Learning models which enable us to assess and optimise marketing and promotion actions.
• Build predictive models including, but not limited to: social behaviour, retention and monetisation to increase the lifetime value of our customers
• Together with technical teams, build pipelines which optimise web promotions, eCRM and in-game experiences.
• Continuously improve our solutions to make them more simple, robust and scalable. This includes pipeline design and continuous improvement schemes through machine learning
• Help provide a collaborative environment in which the team can develop methodologically sound analysis techniques
• Ensure we continue to collect, document and refine relevant data
• Clearly communicate schedule and priorities to stakeholders
• Take a flexible and open-minded approach to new challenges
• Remain alert to opportunities which further utilise our data to benefit the business
• Engage wider analytics and business teams with web data best practices

Key Stakeholders:

Analytics and Insight Department, Senior Management, Game Live Operations

Knowledge & Experience:

Essential:

Competencies:

Proven track record of turning complex business problems into computationally solvable questions.

Practical experience in choosing the right approach according to the problem (being able to choose non-ML approach, simple regression and deep learning)

Skills:

Strong coding ability preferably with SQL, Python or similar which can deliver live solutions.

Familiarity with data science tools (Tensorflow, Scikit-learn) and pipeline design.

Being able to conduct basic supervised and unsupervised methods (linear/logistic regression, decision trees, Random Forests, deep learning or unsupervised problems such as clustering and dimensionality reduction).

Attributes:

You enjoy collaborating with other analysts, data scientists and data engineers to aim at success as a team.

Interpret results from data models and create deliverables that explain the approach and results in simple terms that clients can understand and act on.

Being able to self-manage projects. Prove the business justification of your solutions, create implementation plans and schedules and deliver the robust solution.

Desirable:

Education:

Masters in Data Science, Applied Statistics, Behavioural Economics, Computer Science, Artificial Intelligence, Mathematics, Physics, Engineering or related field.

Experience:

Experience in gaming, retail, banking, advertising, web systems or related field.

Data visualisation experience.

Knowledge:

Understanding of data collection, processing techniques.

Wide knowledge on analytics techniques (Natural language processing, Network analysis, Statistical matching, etc.)

Other:

Commercially minded self-starter with a keen eye for detail

An interest in video games and data analytics

Ability to work under pressure and to deadlines

Continually seeking knowledge and understanding

Understanding of key challenges in our industry